DAYMET Temperature and Precipitation Data
Lee LeBoeuf
10/01/2021
Data Source
The Data Used Here
- Daymet is a data product derived from a collection of algorithms and computer software designed to interpolate and extrapolate from daily meteorological observations to produce gridded estimates of daily weather parameters. Weather parameters generated include daily surfaces of minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length produced on a 1 km x 1 km gridded surface.
- The motivation for producing Daymet is to provide measurements of near-surface meteorological conditions where no instrumentation exists. Having estimates of these surfaces is critical to understanding many processes in the terrestrial biogeochemical system.
- The data shown here includes the monthly average maximum temperature for the months June, July, and August, the average maximum temperature across the entire year, and the annual total precipitation. The data covers years from 1980-2020. The maximum temperature was originally recorded in Celsuis and the precipitation in Millimeters, they were both converted to Fahrenheit and Inches respectively.
- Data are available at the block, block groups, tract, and county levels for Accomack (51001) and Northampton (51131).
- To Learn More, See: Daily Surface Weather and Climatological Summaries
- Below we show summaries of the data at the block group level, and then we show variation by county over time.
Variable descriptions
These summaries are based on data at the block group level from the years 1980-2020. Data are also available at the block, tract, and county levels.
meta %>%
filter(su_blkgp == 1) %>%
select(varname, about) %>% as.list()## $varname
## [1] "STATEFP" "COUNTYFP" "GEOID" "NAMESLAD"
## [5] "CountyName" "year" "June_AvgMaxTF" "July_AvgMaxTF"
## [9] "August_AvgMaxTF" "AvgAnnMaxTemp" "TotpercInch"
##
## $about
## [1] "The federal information processing system (FIPS) codes which are used to identify a geographical location, Virginia is 51"
## [2] "The federal information processing system (FIPS) codes which are used to identify a geographical location, each county has a 3 digit code."
## [3] "The georgraphical ID number of an observation. It is the comnbination of the state FIPS, county FIPS, and the tract, and blockgroup numbers."
## [4] "The georgraphical ID number of an observation"
## [5] "County Name"
## [6] "The data covers years 1980 through 2020"
## [7] "The average maximum temperature for a daily period over the entire monthly period for the month of June. Converted to Fahrenheit during data clean"
## [8] "The average maximum temperature for a daily period over the entire monthly period for the month of July. Converted to Fahrenheit during data clean"
## [9] "The average maximum temperature for a daily period over the entire monthly period for the month of August. Converted to Fahrenheit during data clean"
## [10] "The average maximum temperature for a daily period over the entire year. Converted to Fahrenheit during data clean"
## [11] "The total accumulated precipitation over the monthly period of the daily total precipitation, summed into total yearly precipitation. Sum of all forms of precipitation converted to a water-equivalent depth. Converted to inches during data clean"glimpse(eastdat)## Rows: 82
## Columns: 10
## $ GEOID <int> 51001, 51001, 51001, 51001, 51001, 51001, 51001, 51001, …
## $ year <int> 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 19…
## $ STATEFP <int> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, …
## $ COUNTYFP <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ NAMELSAD <chr> "Accomack County", "Accomack County", "Accomack County",…
## $ June_AvgMaxTF <dbl> 81.16, 84.79, 79.20, 80.26, 83.89, 81.26, 84.13, 83.86, …
## $ July_AvgMaxTF <dbl> 86.56, 86.31, 85.09, 88.25, 83.04, 85.15, 88.73, 88.95, …
## $ Aug_AvgMaxTF <dbl> 86.69, 82.14, 82.09, 85.79, 85.64, 84.22, 82.84, 87.06, …
## $ AvgAnnMaxTF <dbl> 65.69, 65.33, 65.92, 66.34, 66.91, 67.95, 67.44, 66.85, …
## $ TotpercInch <dbl> 35.59, 38.94, 46.54, 47.61, 43.28, 44.36, 32.23, 36.27, …eastdat %>% select(June_AvgMaxTF, July_AvgMaxTF, Aug_AvgMaxTF, AvgAnnMaxTF, TotpercInch) %>%
select(where(~is.numeric(.x))) %>%
as.data.frame() %>%
stargazer(., type = "text", title = "Summary Statistics", digits = 2,
summary.stat = c("mean", "sd", "min", "median", "max"))##
## Summary Statistics
## ===============================================
## Statistic Mean St. Dev. Min Median Max
## -----------------------------------------------
## June_AvgMaxTF 82.65 1.93 78.58 82.46 87.54
## July_AvgMaxTF 86.96 2.07 82.29 86.90 90.96
## Aug_AvgMaxTF 85.04 1.80 81.90 85.50 88.38
## AvgAnnMaxTF 67.58 1.23 65.10 67.46 70.77
## TotpercInch 46.18 7.60 32.23 45.87 66.70
## -----------------------------------------------Visual distribution
These distributions show data at the block group level from the years 1980-2020. Data are also available at the block, tract, and county levels.
longdat <- eastdat %>% select(c(GEOID, June_AvgMaxTF, July_AvgMaxTF, Aug_AvgMaxTF, AvgAnnMaxTF, TotpercInch)) %>% pivot_longer(-GEOID, names_to = "measure", values_to = "value")
longdat$measure <- factor(longdat$measure,
levels = c("June_AvgMaxTF", "July_AvgMaxTF", "Aug_AvgMaxTF", "AvgAnnMaxTF", "TotpercInch"))
longdat %>%
ggplot(aes(x = value, fill = measure)) +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
geom_histogram() +
facet_wrap(~measure, scales = "free")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
meta %>%
filter(varname %in% c("June_AvgMaxTF", "July_AvgMaxTF", "Aug_AvgMaxTF", "AvgAnnMaxTF", "TotpercInch")) %>%
mutate(label = paste0(varname, ": ", about)) %>%
select(label) %>%
as.list()$label [1] "June_AvgMaxTF: The average maximum temperature for a daily period over the entire monthly period for the month of June. Converted to Fahrenheit during data clean"
[2] "July_AvgMaxTF: The average maximum temperature for a daily period over the entire monthly period for the month of July. Converted to Fahrenheit during data clean"
[3] "TotpercInch: The total accumulated precipitation over the monthly period of the daily total precipitation, summed into total yearly precipitation. Sum of all forms of precipitation converted to a water-equivalent depth. Converted to inches during data clean"
Block Group Variation in 2020
All of the following maps show data from the year 2020, but data are available for years 1980-2020.
Average maximum annual temperature
mapdat2020 <- mapdat[which(mapdat$year == 2020),]
pal <- colorNumeric("plasma", reverse = TRUE, domain = mapdat2020$AvgAnnMaxTF)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = mapdat2020,
fillColor = ~pal(mapdat2020$AvgAnnMaxTF),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T),
popup = paste0("GEOID: ", mapdat2020$GEOID, "<br>",
"Temperature in Fahrenhiet: ", mapdat2020$AvgAnnMaxTF)) %>%
leaflet::addLegend("bottomright", pal = pal, values = (mapdat2020$AvgAnnMaxTF),
title = "Average annual <br> temperature <br> in Fahrenheit <br> in 2020", opacity = 0.7)Average maximum August temperature
Monhtly summaries are also available for June and July.
pal <- colorNumeric("plasma", reverse = TRUE, domain = mapdat2020$Aug_AvgMaxTF)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = mapdat2020,
fillColor = ~pal(mapdat2020$Aug_AvgMaxTF),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T),
popup = paste0("GEOID: ", mapdat2020$GEOID, "<br>",
"Temperature in Fahrenhiet: ", mapdat2020$Aug_AvgMaxTF)) %>%
leaflet::addLegend("bottomright", pal = pal, values = (mapdat2020$Aug_AvgMaxTF),
title = "Average August max <br> temperature <br> in Fahrenheit <br> in 2020", opacity = 0.7)Annual precipitation
pal <- colorNumeric("plasma", reverse = TRUE, domain = mapdat2020$TotpercInch)
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = mapdat2020,
fillColor = ~pal(mapdat2020$TotpercInch),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("GEOID: ", mapdat2020$GEOID, "<br>",
"Precipitation in Inches: ", mapdat2020$TotpercInch)
) %>%
leaflet::addLegend("bottomright", pal = pal, values = (mapdat2020$TotpercInch),
title = "Annual precipitation <br>in Inches <br>in 2020", opacity = 0.7)County variation over time
Annual average temperature
dygraph(cville_sf1x, main = "Average maximum annual temperature for each county over time", ylab = "Temperature (F)") %>%
dySeries("Accomack", label = "Accomack") %>%
dySeries("Northampton", label = "Northampton") %>%
dyHighlight(highlightCircleSize = 3,
highlightSeriesBackgroundAlpha = 0.2,
hideOnMouseOut = FALSE, highlightSeriesOpts = list(strokeWidth = 3)) %>%
dyLegend(show = "always", hideOnMouseOut = FALSE, width = 400) %>%
dyRangeSelector(height = 20) %>% dyOptions(colors = RColorBrewer::brewer.pal(6, "Set2"))Average maximum August temperatures
dygraph(cville_sf1x, main = "Average maximum August temperature for each county over time", ylab = "Temperature (F)") %>%
dySeries("Accomack", label = "Accomack") %>%
dySeries("Northampton", label = "Northampton") %>%
dyHighlight(highlightCircleSize = 3,
highlightSeriesBackgroundAlpha = 0.2,
hideOnMouseOut = FALSE, highlightSeriesOpts = list(strokeWidth = 3)) %>%
dyLegend(show = "always", hideOnMouseOut = FALSE, width = 400) %>%
dyRangeSelector(height = 20) %>% dyOptions(colors = RColorBrewer::brewer.pal(6, "Set2"))Annual precipitation
dygraph(cville_sf1x, main = "Annual precipitation for each county over time", ylab = "Precipitation (In)") %>%
dySeries("Accomack", label = "Accomack") %>%
dySeries("Northampton", label = "Northampton") %>%
dyHighlight(highlightCircleSize = 3,
highlightSeriesBackgroundAlpha = 0.2,
hideOnMouseOut = FALSE, highlightSeriesOpts = list(strokeWidth = 3)) %>%
dyLegend(show = "always", hideOnMouseOut = FALSE, width = 400) %>%
dyRangeSelector(height = 20) %>% dyOptions(colors = RColorBrewer::brewer.pal(6, "Set2"))